
NVIDIA A100 8x80GB Baseboard
Price range: 10€ through 100€
Delivery is made within 14-21 days
The prices are presented for both corporate clients and individuals.
Pricing for
The prices are presented for both corporate clients and individuals.
NVIDIA A100 8×80GB Baseboard. 8×A100 80GB SXM—balanced training/inference pod with NVSwitch. Direct import, official warranty, crated shipping, 7–10-day delivery.
Pairs well with
Product description
8×NVIDIA A100 80GB SXM GPU Baseboard: Ultimate Power for AI and HPC
8×NVIDIA A100 SXM 80GB GPU Baseboard is a high-density compute module that integrates eight NVIDIA A100 GPUs with 80 GB of HBM2e memory each — providing a total of 640 GB of ultra-fast memory and immense computational throughput for artificial intelligence, data analytics, and high-performance computing (HPC) workloads.
Unlike traditional PCIe configurations, GPUs within this baseboard are interconnected via NVLink and NVSwitch, enabling direct high-bandwidth communication between all eight accelerators. This design allows them to operate as a unified system, eliminating PCIe bottlenecks and maximizing parallel efficiency for the most demanding AI and scientific applications.
Specifications
- Total GPU Memory: 640 GB HBM2e
- Memory per GPU: 80 GB HBM2e
- GPU Count: 8× NVIDIA A100 (SXM4 form factor)
- Memory Bandwidth: up to 2 TB/s per GPU
- GPU Interconnect: NVLink with NVSwitch — up to 600 GB/s per link
- Architecture: NVIDIA Ampere
- Interface: PCIe Gen4 (integration-ready baseboard)
- Cooling: Passive, optimized for rack-mounted servers
Key Advantages
- Unified GPU architecture. NVSwitch connects all GPUs into a single compute matrix — essential for LLM training and generative AI workloads.
- Extreme performance and reliability. Up to 2 TB/s memory bandwidth and hundreds of GB/s inter-GPU throughput ensure consistent scalability.
- Infrastructure efficiency. Shared power and cooling systems reduce total energy consumption and simplify deployment.
- Seamless scalability. Multiple baseboards can be interconnected to form full AI clusters for large-scale model training or HPC tasks.
Applications
- Large Language Models (LLMs). Training and inference of GPT, DeepSeek, Qwen, Mistral, and other advanced architectures.
- HPC Simulations. Molecular modeling, energy research, CFD, and climate simulation workloads.
- Data Centers. High-density GPU racks and cloud compute environments.
- Generative AI. Training multimodal and complex generative systems with high data throughput.
Why Choose 8×NVIDIA A100 80GB SXM Baseboard
- Eight A100 GPUs in one module — delivering supercomputer-class performance.
- Higher efficiency and bandwidth compared to eight separate PCIe GPUs, thanks to NVLink/NVSwitch.
- Reduced setup time and operational overhead for heavy AI and HPC workloads.
- OEM baseboard offers DGX-class architecture at a lower infrastructure cost.
8×NVIDIA A100 SXM 80GB GPU Baseboard is a foundational building block for modern data centers and AI clusters. It provides unmatched performance, scalability, and efficiency — an ideal solution for enterprises and research institutions advancing large-scale AI, simulation, and scientific computing projects.
Additional information
| Weight | 1,8 kg |
|---|---|
| Dimensions | 26,7 × 11,1 cm |
| Country of manufacture | Taiwan |
| Manufacturer's warranty (years) | 1 |
| Model | NVIDIA A100 |
| Cache L2 (MB) | 40 |
| Process technology (nm) | 4 |
| Memory type | HBM2e |
| Graphics Processing Unit (Chip) | |
| Number of CUDA cores | 6912 |
| Number of Tensor cores | 432 |
| Video memory size (GB) | 80 |
| Memory frequency (MHz) | 16000 |
| Memory bus width (bits) | 5120 |
| Memory Bandwidth (GB/s) | 2039 |
| Connection interface (PCIe) | PCIe 5.0 x16 |
| FP16 performance (TFLOPS) | 312 |
| FP32 performance (TFLOPS) | 156 |
| FP64 performance (TFLOPS) | 9.7 |
| Cooling type | Passive (server module) |
| Number of occupied slots (pcs) | 8 |
| Length (cm) | 26.7 |
| Width (cm) | 11.1 |
| Weight (kg) | 1.8 |
| Temperature range (°C) | 0–85 |
| NVLink Throughput (GB/s) | 600 |
| Multi-GPU support | Yes (NVSwitch) |
| Virtualization/MIG support | MIG (up to 7 instances) |
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